Fundamental insights into the molecular action of oncogenes and tumor suppressor genes are being translated into a new generation of anti-cancer drugs that target specific cell signaling pathways. We hypothesize that the genetic background of malignant gliomas will dictate (and ultimately predict) the response to these signal transduction inhibitors. The broad objective of this project is to test this hypothesis by exploiting an important opportunity. Our group is involved in the initial clinical trial with a signal transduction inhibitor, the platelet-derived growth factor receptor (PDGFR)/abl blocker STI571 (Gleevec), in gliomas. We have access to clinical samples from this trial and we are in position to correlate genetic data with clinical responses. The project has two specific aims: Specific Aim 1 is to determine whether clinical responses to Gleevec correlate with any of the major stereotypical and well-characterized genetic cohorts of glioma: 1) EGF receptor (EGFR) gene amplification, 2) p53 loss-of-function mutation, 3) loss-of-function PTEN mutations and 4) p16/CDKN2A deletion. In addition, we will examine the sequence of the PDGFR kinase domain for potential mutations that may associate with drug refractoriness. Specific Aim 1 insures that a new generation of "smart drugs" is given a fair opportunity to succeed. Even if this drug fails clinical trials, it will be important to know that it was tested on a representative number of gliomas from each of the major genetic cohorts. Specific Aim 2 is to screen for novel, unanticipated genetic lesions that may correlate with response to Gleevec. Specific Aim 2 addresses a potential pitfall with the first specific aim: What if the drugs prove to be effective on a subset of patients - but that subset does not correspond to any of the stereotypical genetic cohorts? Single nucleotide polymorphism (SNP) arrays will be used to screen for novel lesions because, in most cases, the tumor samples for this project will be available as archival tissue only. SNP array analysis will not only provide an independent test of the hypothesis that the genetic background of a glioma determines the response to signal transduction inhibitors, but it may also identify useful new prognostic indicators for these tumors.